IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i19p5189-d269570.html
   My bibliography  Save this article

The Impact of High-Tech Industry Agglomeration on Green Economy Efficiency—Evidence from the Yangtze River Economic Belt

Author

Listed:
  • Weiliang Chen

    (School of Management, Nanchang University, Nanchang 330031, China
    Department of City and Regional Planning, University of North Carolina at Chapel Hill, Chapel Hill, NC 27517, USA)

  • Xinjian Huang

    (School of Management, Nanchang University, Nanchang 330031, China
    School of Economics and Management, Nanchang University, Nanchang 330031, China)

  • Yanhong Liu

    (School of Management, Nanchang University, Nanchang 330031, China
    Department of City and Regional Planning, University of North Carolina at Chapel Hill, Chapel Hill, NC 27517, USA)

  • Xin Luan

    (Department of City and Regional Planning, University of North Carolina at Chapel Hill, Chapel Hill, NC 27517, USA
    School of Transportation, Southeast University, Nanjing 211189, China)

  • Yan Song

    (Department of City and Regional Planning, University of North Carolina at Chapel Hill, Chapel Hill, NC 27517, USA)

Abstract

Development is the eternal theme of the times. However, the transformation of the development mode is imminent, and we should abandon the extensive economic development mode and turn to the efficient development of an intensive mode. The high-tech industry will be the decisive force in future industrial development. The agglomeration of the industry will help form economies of scale, thereby improving the effective allocation of resources and promoting productivity. The increase in green economy efficiency is a key factor in achieving green development and an important indicator of achieving the coordinated development of economic development and environmental protection. Therefore, in this study, we try to improve the efficiency of the green economy through industrial agglomeration to achieve green development. In order to solve this problem, we took the Yangtze River Economic Belt as the research object, used Super Slacks-based Measure (SBM) data envelopment analysis (DEA) and general algebraic modeling system (GAMS) to study the green economy efficiency, and then used the system generalized moment method (SGMM) to study the impact of high-tech industry agglomeration on green economy efficiency. According to the empirical test, we found that (1) the green economy efficiency of the Yangtze River Economic Belt shows a volatile upward trend, (2) the green economy efficiency of the Yangtze River Economic Belt differs with time and by region, (3) the agglomeration of the high-tech industry has a lagging effect on the improvement of green economy efficiency, and (4) the regression coefficients of economic development and foreign direct investment are positive and those of environmental regulation and urbanization are negative. Finally, in this paper, we provide corresponding policy recommendations to promote the agglomeration of high-tech industries, thereby improving the efficiency of the green economy.

Suggested Citation

  • Weiliang Chen & Xinjian Huang & Yanhong Liu & Xin Luan & Yan Song, 2019. "The Impact of High-Tech Industry Agglomeration on Green Economy Efficiency—Evidence from the Yangtze River Economic Belt," Sustainability, MDPI, vol. 11(19), pages 1-18, September.
  • Handle: RePEc:gam:jsusta:v:11:y:2019:i:19:p:5189-:d:269570
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/19/5189/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/11/19/5189/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kalinic, Zoran & Marinkovic, Veljko & Molinillo, Sebastián & Liébana-Cabanillas, Francisco, 2019. "A multi-analytical approach to peer-to-peer mobile payment acceptance prediction," Journal of Retailing and Consumer Services, Elsevier, vol. 49(C), pages 143-153.
    2. Barrios, Salvador & Bertinelli, Luisito & Strobl, E. & Teixeira, Antonio-Carlos, 2005. "The dynamics of agglomeration: evidence from Ireland and Portugal," Journal of Urban Economics, Elsevier, vol. 57(1), pages 170-188, January.
    3. Yanhong Liu & Xinjian Huang & Weiliang Chen, 2019. "Threshold Effect of High-Tech Industrial Scale on Green Development—Evidence from Yangtze River Economic Belt," Sustainability, MDPI, vol. 11(5), pages 1-21, March.
    4. Yongfeng Zhu & Zilong Wang & Shilei Qiu & Lingling Zhu, 2019. "Effects of Environmental Regulations on Technological Innovation Efficiency in China’s Industrial Enterprises: A Spatial Analysis," Sustainability, MDPI, vol. 11(7), pages 1-19, April.
    5. Lee & Yi & Park, 2013. "Impact of the Global Financial Crisis on the Degree of Financial Integration among East Asian Countries," Global Economic Review, Taylor & Francis Journals, vol. 42(4), pages 425-459, December.
    6. Miller, Stephen M. & Upadhyay, Mukti P., 2000. "The effects of openness, trade orientation, and human capital on total factor productivity," Journal of Development Economics, Elsevier, vol. 63(2), pages 399-423, December.
    7. Gilles Duranton & Diego Puga, 2000. "Diversity and Specialisation in Cities: Why, Where and When Does it Matter?," Urban Studies, Urban Studies Journal Limited, vol. 37(3), pages 533-555, March.
    8. Jianlong Wu & Zhongji Yang & Xiaobo Hu & Hongqi Wang & Jing Huang, 2018. "Exploring Driving Forces of Sustainable Development of China’s New Energy Vehicle Industry: An Analysis from the Perspective of an Innovation Ecosystem," Sustainability, MDPI, vol. 10(12), pages 1-24, December.
    9. Stephen R. Bond, 2002. "Dynamic panel data models: a guide to micro data methods and practice," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 1(2), pages 141-162, August.
    10. Henderson, Vernon, 1997. "Externalities and Industrial Development," Journal of Urban Economics, Elsevier, vol. 42(3), pages 449-470, November.
    11. Nobuhiro Hosoe & Kenji Gasawa & Hideo Hashimoto, 2010. "Textbook of Computable General Equilibrium Modelling," Palgrave Macmillan Books, Palgrave Macmillan, number 978-0-230-28165-3, December.
    12. Alexandra Tsvetkova & Jean-Claude Thill & Deborah Strumsky, 2014. "Metropolitan innovation, firm size, and business survival in a high-tech industry," Small Business Economics, Springer, vol. 43(3), pages 661-676, October.
    13. Pleydell, David R.J. & Chrétien, Stéphane, 2010. "Mixtures of GAMs for habitat suitability analysis with overdispersed presence/absence data," Computational Statistics & Data Analysis, Elsevier, vol. 54(5), pages 1405-1418, May.
    14. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    15. K Tone, 2002. "A strange case of the cost and allocative efficiencies in DEA," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(11), pages 1225-1231, November.
    16. Cieślik Andrzej & Ghodsi Mahdi, 2015. "Agglomeration externalities, market structure and employment growth in high-tech industries: Revisiting the evidence," Miscellanea Geographica. Regional Studies on Development, Sciendo, vol. 19(3), pages 76-81, September.
    17. Christoph Alsleben, 2005. "The Downside of Knowledge Spillovers: An Explanation for the Dispersion of High-tech Industries," Journal of Economics, Springer, vol. 84(3), pages 217-248, May.
    18. Qi Fan & Hahui Hu, 2015. "The Impact of Vertical Specialization on the Agglomeration of China’s Manufacturing Sector: An Empirical Research Based on Province Level Panel Data," Eurasian Studies in Business and Economics, in: Mehmet Huseyin Bilgin & Hakan Danis & Ender Demir & Chi Keung Marco Lau (ed.), Innovation, Finance, and the Economy, edition 127, pages 213-225, Springer.
    19. Hironobu Miyazaki, 2009. "An analysis of the relation between R&D and M&A in high-tech industries," Applied Economics Letters, Taylor & Francis Journals, vol. 16(2), pages 199-201.
    20. Stephen Bond, 2002. "Dynamic panel data models: a guide to microdata methods and practice," CeMMAP working papers CWP09/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    21. Merchant, John E., 1997. "The role of governments in a market economy: Future strategies for the high-tech industry in America," International Journal of Production Economics, Elsevier, vol. 52(1-2), pages 117-131, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mingzhi Zhang & Xiangyu Zhou & Chao Chen & Jianxu Liu & Jiaxi Li & Fuying Huan & Bowen Wang, 2023. "Enterprise Spatial Agglomeration and Economic Growth in Northeast China: Policy Implications for Uneven to Sustainable Development," Sustainability, MDPI, vol. 15(15), pages 1-17, July.
    2. Lei Gao & Taowu Pei & Tielong Wang & Yue Hao & Chao Li & Yu Tian & Xu Wang & Jingran Zhang & Weiming Song & Chao Yang, 2020. "What Type of Industrial Agglomeration Is Beneficial to the Eco-Efficiency of Northwest China?," Sustainability, MDPI, vol. 13(1), pages 1-15, December.
    3. Lindong Ma & Yuanxiao Hong & Xihui Chen, 2022. "Can Green Economy and Ecological Welfare Achieve Synergistic Development? The Perspective of the “Two Mountains” Theory," IJERPH, MDPI, vol. 19(11), pages 1-24, May.
    4. Qian Zhang & Decai Tang & Brandon J. Bethel, 2021. "Yangtze River Basin Environmental Regulation Efficiency Based on the Empirical Analysis of 97 Cities from 2005 to 2016," IJERPH, MDPI, vol. 18(11), pages 1-22, May.
    5. Ying Song & Lu Yang & Stavros Sindakis & Sakshi Aggarwal & Charles Chen, 2023. "Analyzing the Role of High-Tech Industrial Agglomeration in Green Transformation and Upgrading of Manufacturing Industry: the Case of China," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 14(4), pages 3847-3877, December.
    6. Chengwei Wang & Qingchun Meng, 2020. "Research on the Sustainable Synergetic Development of Chinese Urban Economies in the Context of a Study of Industrial Agglomeration," Sustainability, MDPI, vol. 12(3), pages 1-15, February.
    7. Jiaoping Yang & Shujun Wang & Shan Sun & Jianhua Zhu, 2022. "Influence Mechanism of High-Tech Industrial Agglomeration on Green Innovation Performance: Evidence from China," Sustainability, MDPI, vol. 14(6), pages 1-20, March.
    8. Shangram Bahadur Shah & Jirakiattikul Sopin & Kua-Anan Techato & Bibek Kumar Mudbhari, 2023. "A Systematic Review on Nexus Between Green Finance and Climate Change: Evidence from China and India," International Journal of Energy Economics and Policy, Econjournals, vol. 13(4), pages 599-613, July.
    9. Rui Jiang & Chunxue Liu & Xiaowei Liu & Shuai Zhang, 2022. "Space–Time Effect of Green Total Factor Productivity in Mineral Resources Industry in China: Based on Space–Time Semivariogram and SPVAR Model," Sustainability, MDPI, vol. 14(14), pages 1-16, July.
    10. Lei Gao & Fang Li & Jingran Zhang & Xu Wang & Yue Hao & Chao Li & Yu Tian & Chao Yang & Weiming Song & Tielong Wang, 2021. "Study on the Impact of Industrial Agglomeration on Ecological Sustainable Development in Southwest China," Sustainability, MDPI, vol. 13(3), pages 1-13, January.
    11. Weisong Mi & Kaixu Zhao & Pei Zhang, 2022. "Spatio-Temporal Evolution and Driving Mechanism of Green Innovation in China," Sustainability, MDPI, vol. 14(9), pages 1-27, April.
    12. Wang, Jianda & Dong, Xiucheng & Dong, Kangyin, 2022. "How does ICT agglomeration affect carbon emissions? The case of Yangtze River Delta urban agglomeration in China," Energy Economics, Elsevier, vol. 111(C).
    13. Lei Gao & Junxuan Guo & Xu Wang & Yu Tian & Tielong Wang & Jingran Zhang, 2022. "Research on the Influence of Different Types of Industrial Agglomeration on Ecological Efficiency in Western China," Sustainability, MDPI, vol. 14(21), pages 1-13, November.
    14. Yake Gao & Yawei Zhang & Kelly Yujie Wang & Tsz Leung Yip, 2023. "Exploring the Carbon-Mitigation Effect of High-Speed Railway and Its Underlying Mechanism," Sustainability, MDPI, vol. 15(17), pages 1-17, August.
    15. Wei, Wei & Zhang, Wan-Li & Wen, Jun & Wang, Jun-Sheng, 2020. "TFP growth in Chinese cities: The role of factor-intensity and industrial agglomeration," Economic Modelling, Elsevier, vol. 91(C), pages 534-549.
    16. Lu Zhang & Renyan Mu & Shuhua Hu & Quan Zhang & Song Wang, 2021. "Impacts of Manufacturing Specialized and Diversified Agglomeration on the Eco-Innovation Efficiency—A Nonlinear Test from Dynamic Perspective," Sustainability, MDPI, vol. 13(7), pages 1-27, March.
    17. Ran Feng & Xiaoe Qu, 2023. "Innovation-Driven Industrial Agglomeration Impact on Green Economic Growth in the Yellow River Basin: An Empirical Analysis," Sustainability, MDPI, vol. 15(17), pages 1-24, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhou, Xiaoyan & Zhang, Jie & Li, Junpeng, 2013. "Industrial structural transformation and carbon dioxide emissions in China," Energy Policy, Elsevier, vol. 57(C), pages 43-51.
    2. Brülhart, Marius & Mathys, Nicole A., 2008. "Sectoral agglomeration economies in a panel of European regions," Regional Science and Urban Economics, Elsevier, vol. 38(4), pages 348-362, July.
    3. Bravo-Ortega, Claudio & García Marín, Álvaro, 2011. "R&D and Productivity: A Two Way Avenue?," World Development, Elsevier, vol. 39(7), pages 1090-1107, July.
    4. Martin Andersson & Hans Lööf, 2011. "Agglomeration and productivity: evidence from firm-level data," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 46(3), pages 601-620, June.
    5. Constantin Belu & Cristiana Manescu, 2013. "Strategic corporate social responsibility and economic performance," Applied Economics, Taylor & Francis Journals, vol. 45(19), pages 2751-2764, July.
    6. Giulio Cainelli & Sandro Montresor & Giuseppe Vittucci Marzetti, 2014. "Spatial agglomeration and firm exit: a spatial dynamic analysis for Italian provinces," Small Business Economics, Springer, vol. 43(1), pages 213-228, June.
    7. Thanh Pham Thien Nguyen & Son Hong Nghiem & Eduardo Roca, 2016. "Management Behaviour in Vietnamese Commercial Banks," Australian Economic Papers, Wiley Blackwell, vol. 55(4), pages 345-367, December.
    8. Kofi Adjei-Frimpong & Christopher Gan & Baiding Hu, 2014. "Cost Efficiency of Ghana's Banking Industry: A Panel Data Analysis," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 8(2), pages 69-86.
    9. Díez-Esteban, José María & Farinha, Jorge Bento & García-Gómez, Conrado Diego, 2016. "The role of institutional investors in propagating the 2007 financial crisis in Southern Europe," Research in International Business and Finance, Elsevier, vol. 38(C), pages 439-454.
    10. Eicher, Theo S. & Schreiber, Till, 2010. "Structural policies and growth: Time series evidence from a natural experiment," Journal of Development Economics, Elsevier, vol. 91(1), pages 169-179, January.
    11. Kieran McQuinn & Karl Whelan, 2007. "Solow ( 1956 ) as a model of cross-country growth dynamics," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 23(1), pages 45-62, Spring.
    12. Manthos D. Delis & Sotirios Kokas & Steven Ongena, 2016. "Foreign Ownership and Market Power in Banking: Evidence from a World Sample," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 48(2-3), pages 449-483, March.
    13. Jessica M. Mc Lay & Roy Lay-Yee & Barry J. Milne & Peter Davis, 2015. "Regression-Style Models for Parameter Estimation in Dynamic Microsimulation: An Empirical Performance Assessment," International Journal of Microsimulation, International Microsimulation Association, vol. 8(2), pages 83-127.
    14. Philippe Martin & Thierry Mayer & Florian Mayneris, 2008. "Spatial Concentration and Firm-Level Productivity in France," Sciences Po publications 6858, Sciences Po.
    15. Huy Quang Doan, 2019. "Trade, Institutional Quality and Income: Empirical Evidence for Sub-Saharan Africa," Economies, MDPI, vol. 7(2), pages 1-23, May.
    16. Lee, Chien-Chiang & Yang, Shih-Jui & Chang, Chi-Hung, 2014. "Non-interest income, profitability, and risk in banking industry: A cross-country analysis," The North American Journal of Economics and Finance, Elsevier, vol. 27(C), pages 48-67.
    17. Melissa Dell & Benjamin F. Jones & Benjamin A. Olken, 2014. "What Do We Learn from the Weather? The New Climate-Economy Literature," Journal of Economic Literature, American Economic Association, vol. 52(3), pages 740-798, September.
    18. Carlos Carreira & Luís Lopes, 2016. "Collecting new pieces to the regional knowledge spillovers puzzle: high-tech versus low-tech industries," GEMF Working Papers 2016-06, GEMF, Faculty of Economics, University of Coimbra.
    19. Jose Garcia-Louzao & Linas Tarasonis, 2023. "Productivity-enhancing reallocation during the Great Recession: evidence from Lithuania," Oxford Economic Papers, Oxford University Press, vol. 75(3), pages 729-749.
    20. Maynou, L. & McGuire, A. & Serra-Sastre, V., 2019. "Exploring the Impact of New Medical Technology on Workforce Planning," Working Papers 19/07, Department of Economics, City University London.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:11:y:2019:i:19:p:5189-:d:269570. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.